Our results of the average [99mTc]Tc-ECD clearance rate in normal whole brain was − 3.15 % ± 0.55 %/hr. This mean rate was slightly slower than in Léveillé, et al (∼ -6%/hr) and Ischise, et al (-4.3% ± 1.7%/hr) studies (Leveille et al., 1989; Ichise et al., 1997). The thalamic clearance rate was slower than other brain regions in all three subjects, which is similar to the study by Ischise, et al. However, there was no statistically significant difference among regions in our study. The occipital clearance rate was similar to the rest of the brain regions, unlike Ischise’s study whose findings showed significantly faster washout at this region. A possible explanation is the difference in methodological techniques such as image reconstruction and/or image analysis (curve fitting technique: monoexponential vs linear regression, or different ROIs templates: AAL atlas vs ellipses). Moreover, our rates were calculated from only three normal subjects, in contrast to twenty subjects used in their study.
The average whole brain ECD clearance rates of patients with DRE were − 2.52 to -3.74 % in ictal, aura and interictal states, which were much slower than the clearance rate of DRE patients in Grunwald, et al’ s study (-8.9 to -13.5%) (Grunwald et al., 1994). There are 2 possible explanations for this matter. Firstly, there were some differences in the aspects of acquisition time, namely number of serial SPECT scans (2-time vs 7-time point) and duration of scan (about 70 vs 240 minutes). Secondly, different ROI techniques were used. Grunwald’s study might include soft tissue or background activities in their ROI, that may cause fast washout in their study. Therefore, there might be actual difference between early and late clearance rates or the clearance rate difference may be the result of interfered rapid soft tissue and background activities washout.
In contrast to other studies, our study further focused on the SOZ. We analyzed the SOZ using 2 methods: 1) comparison of epilepsy states in the same SOZ, and 2) comparison of SOZ with contralateral region in ictal, aura, and interictal states. In the former method, the average ECD clearance rate of the SOZs in ictal state showed a statistically significant difference (p < 0.001) from aura, interictal, and normal, while there was no statistically significant difference among aura, interical and normal (Table 3). This information shows that by using the first method, ictal state is crucial for comparison with other states to identify SOZ. The area with different clearance pattern from either interictal or aura state or normal brain is likely to be a SOZ. In the latter method, the SOZs showed statistically significant differences from the contralateral regions with p = 0.039 in interictal state (Fig. 4). No statistically significant difference in aura state was detected. This is likely resulted from a small sample size (N = 2) in aura state. Since the clearance pattern of aura is similar to interictal state, adding aura to interictal state would result in statistically significant difference from the contralateral regions with p = 0.011. Thus, by using the latter method, either interictal or aura SPECT study may be used independently from ictal SPECT study when there is unavailable ictal SPECT study.
By visual analysis, clearance patterns those had localization performance were washin and slow washout patterns in ictal slope maps, fast washout patterns in aura slope maps and interictal slope maps. Washout rate was mentioned ‘‘slower’’ in the ictal onset zone (hyperperfused areas) than other brain areas in Grünwald F, et al. study. Surprisingly, our study also found washin patterns other than slow washout. Some probable explanations were that there might be some alteration in BBB permeability, regional cerebral blood flow and/or esterase activity causing more retention of [99mTc]Tc-ECD in the brain cells during ictal period and hours thereafter. Fast washout pattern was observed only in aura and interictal slope map. Mechanism of fast washout was probably due to low esterase activity in the SOZs, resulting in reduced ECD retention which was previously explained in vitro by Jacquier-Sarlin, et al’s study (Jacquier-Sarlin et al., 1996). Aura also showed fast washout, which is similar to interictal slope map pattern. This may be explained by the state of aura itself, which is a subjective ictal phenomenon without definite ictal EEG onset, and thus resulting in patterns mimicking interictal state.
From our hospital statistics in the last 5 years, 40 % of patients with DRE failed to complete both ictal and interical SPECT scans while they were hospitalized for video-EEG monitoring, resulting in only available interictal SPECT study which is almost useless for SOZ localization by conventional SPECT method. In this study, two of seven patients could not perform ictal SPECT because of rare seizure frequency. We have shown that multiple time points interictal SPECT scan is also useful and can improve SOZ localization as compared to only one-time point conventional interictal scan. Thus, having only interictal scan, SOZ can still be diagnosed if fast washout pattern is seen on serial SPECT interictal scan (Table 3, Fig. 3).
From our data, SOZ localization using slope maps showed that this method had better performance when compared to conventional imaging methods (Table 4). Thus, it is a promising method to increase percent localization of SOZ and should be performed in patients with discordant results of conventional pre-surgical investigations.
Limitation and recommendation
Correlation between injection time and clearance patterns or localization performance, which is one factor that affected biodistribution of ECD, could not be done due to the small sample size. For technical aspects, there are some drawbacks of this method: 1) Patients need to stay still during each static scan in order to complete serial SPECT scan. 2) Scan time was increased up to 4 hours from the routine 30–60 minutes, which may cause machine availability problems in the center with limited number of SPECT machines. Future study using 2 time points for clearance pattern analysis may be more practical in routine clinical practice. Analysis of clearance pattern in different pathology may provide better understanding of biodistribution of radiotracer in patient with DRE.